In situ training of an in-sensor artificial neural network based on ferroelectric photosensors

In situ training of an in-sensor artificial neural network based on ferroelectric photosensors

Abstract In-sensor computing has emerged as an ultrafast and low-power technique for next-generation machine vision. However, in situ training of in-sensor computing systems remains challenging due to the demands for both high-performance devices and efficient programming schemes. Here, we experimen...

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Main Authors: Haipeng Lin, Jiali Ou, Zhen Fan, Xiaobing Yan, Wenjie Hu, Boyuan Cui, Jikang Xu, Wenjie Li, Zhiwei Chen, Biao Yang, Kun Liu, Linyuan Mo, Meixia Li, Xubing Lu, Guofu Zhou, Xingsen Gao, Jun-Ming Liu
Format: Article
Language:English
Published: Nature Portfolio 2025-01-01
Series:Nature Communications
Online Access:https://doi.org/10.1038/s41467-024-55508-z
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https://doi.org/10.1038/s41467-024-55508-z

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